CONSTRUCTING A DATA WAREHOUSE FOR NUTRITION CLINICAL STUDIES
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1 CONSTRUCTING A DATA WAREHOUSE FOR NUTRITION CLINICAL STUDIES Paul Vervuren PhUSE Barcelona October 10 th, 2016
2 CLINICAL DATA WAREHOUSE PROJECT
3 PART OF DANONE FOUR DIVISIONS WATERS MEDICAL NUTRITION FRESH DAIRY EARLY LIFE NUTRITION Bring health through food to as many people as possible
4 THE FIRST 1000 DAYS AN IMPACT ON LATER LIFE HEALTH -9m to 24m Critical window of opportunity to support healthy later life HEALTHY Altered growth and development Stunting Allergy Obesity Coronary heart disease Diabetes Cognitive decline DISEASE CONCEPTION TODDLERHOOD ADULTHOOD
5 A BABY IS NOT A SMALL ADULT THE ORGANS OF A NEWBORN BABY STILL NEED TO DEVELOP Immaturity of: GUT MICROBIOTICA IMMUNE SYSTEM METABOLISM DIGESTIVE SYSTEM BRAIN BONES
6 THE SCIENCE OF NUTRITION DIFFERENCES IN ACTION REQUIRE SPECIFIC RESEARCH APPROACH FOCUSED LARGE EFFECT ON SINGLE TARGET CUMULATIVE EFFECTS ON MULTIPLE TARGETS
7 QUOTES FROM PROGRAMMERS AND STATISTICIANS Analyses of secondary parameters leads to surprising and very interesting patterns! Many exploratory endpoints and analyses No NDAs, thus no external incentive to standardize clinical trial data across studies Long-term follow-up in quite a number of studies Open-minded culture, with standards and processes still developing and maturing Not the standard Phase I-IV trials, and fewer trials for one product than in Pharma, but each trial investigates many outcomes
8 DATA STANDARDIZATION AND INTEGRATION Study A Study C Study B SDTM Product composition ADaM Individual raw study data Standardized raw data Standardized analysisready data
9 GROWTH DATA VITAL SIGNS (VS) randomno weightinf_w4 lengthinf_w4 headcirc_w4 weighinf_w8 Study A VISIT USUBJID VSTEST VSORRES VSORRESU Study C Study B PID VISIT HEIG HEIGU WEIG WEIGU
10 GROWTH DATA VITAL SIGNS (VS) Study C SDTM VISIT USUBJID VSTEST VSORRES VSORRESU DOMAIN USUBJID VSTESTCD VSTEST VSORRES VSORRESU VISIT
11 ONE STEP AWAY FROM GROWTH ANALYSES SDTM.VS SDTM ADaM SDTM.DM WHO reference data Age -1SD Median +1SD ADAM.ADVS
12 PRODUCT COMPOSITION AS DATA SDTM Product composition Product Characteristic Product Characteristic Category Product Characteristic Description PRDCHAR CHARCAT CHARDESC PREB10 Prebiotics Prebiotics lcfos PREB20 Prebiotics Prebiotics scgos PROT1.8 Protein Protein at 1.8g/100kcal Unique Product Identifier Unique Product Full Description Product Characteristics Space Delimited List From CT UPRODID UPROD PRDCHAR CFLP00 Low Protein Cow's Milk Infant Formula with a protein content of 1.8 g/100kcal PROT1.8 CFLP10 Modified Low Protein Cow's Milk Infant Formula with a protein content of 1.8 g/100kcal with ferments and scgos/icfos PROT1.8 PREB10 PREB20 FERM Planned treatment (ARM/TRT01P) Analysis Record Flag (ANLzzFL)
13 ANALYSIS ENGINE What is the effect of ingredient xx on growth across all studies? (and I want a p-value) Study A Study C Study B SDTM Product composition ADaM Individual raw study data Standardized raw data Standardized analysisready data
14 SPECIFIC DOMAINS IN NUTRITION CLINICAL STUDIES Many common domains: DM, AE, CM, MH, LB Typical: GI-tolerance Microbiota data Food intake Parent data
15 GI?
16 GI
17 GI TOLERANCE Visit 1 Baseline Gastrointestinal tolerance CRF example Does the child / the subject suffer from: Nausea Absent Mild Moderate Severe Vomiting Absent Mild Moderate Severe Burping Absent Mild Moderate Severe Flatulence Absent Mild Moderate Severe Diarrhoea Absent Mild Moderate Severe Constipation Absent Mild Moderate Severe Colic (cramps) Absent Mild Moderate Severe Regurgitation Absent Mild Moderate Severe Average number of stools per day: What is the average consistency of the stools? Watery Soft, puddinglike Soft, formed Dry, formed Dry, hard pellets
18 GI TOLERANCE Visit 1 Baseline Gastrointestinal tolerance CRF example Does the child / the subject suffer from: Nausea Absent Mild Moderate Severe Vomiting Absent Mild Moderate Severe Burping Absent Mild Moderate Severe Flatulence Absent Mild Moderate Severe Diarrhoea Absent Mild Moderate Severe Constipation Absent Mild Moderate Severe Colic (cramps) Absent Mild Moderate Severe Regurgitation Absent Mild Moderate Severe Average number of stools per day: What is the average consistency of the stools? Watery Soft, puddinglike Soft, formed Dry, formed Dry, hard pellets
19 GENERAL OBSERVATION CLASSES (SDTM-IG 2.1) The Interventions class captures investigational, therapeutic and other treatments that are administered to the subject (with some actual or expected physiological effect) either as specified by the study protocol (e.g., exposure to study drug), coincident with the study assessment period (e.g., concomitant medications), or self-administered by the subject (such as use of alcohol, tobacco, or caffeine). The Events class captures planned protocol milestones such as randomization and study completion, and occurrences, conditions, or incidents independent of planned study evaluations occurring during the trial (e.g., adverse events) or prior to the trial (e.g., medical history). The Findings class captures the observations resulting from planned evaluations to address specific tests or questions such as laboratory tests, ECG testing, and questions listed on questionnaires.
20 GI TOLERANCE CRF example Visit 1 Baseline Gastrointestinal tolerance Does the child / the subject suffer from: CETERM CEPRESP= Y X Nausea Absent Mild Moderate Severe Vomiting Absent Mild Moderate Severe Burping Absent Mild Moderate Severe Flatulence Absent Mild Moderate Severe X X X X Diarrhoea Absent Mild Moderate Severe Constipation Absent Mild Moderate Severe Colic (cramps) Absent Mild Moderate Severe Regurgitation Absent Mild Moderate Severe CEOCCUR= N X X X CEOCCUR= Y CESEV DOMAIN USUBJID CETERM CECAT CEPRESP CEOCCUR CESEV CE XXX NAUSEA GASTROINTESTINAL TOLERANCE Y N CE XXX VOMITING GASTROINTESTINAL TOLERANCE Y Y MILD CE XXX BURPING GASTROINTESTINAL TOLERANCE Y Y MODERATE CE XXX FLATULENCE GASTROINTESTINAL TOLERANCE Y Y MILD
21 GI TOLERANCE CRF example Visit 1 Baseline Gastrointestinal tolerance Does the child / the subject suffer from: Nausea Absent Mild Moderate Severe Vomiting Absent Mild Moderate Severe Burping Absent Mild Moderate Severe Flatulence Absent Mild Moderate Severe Diarrhoea Absent Mild Moderate Severe Constipation Absent Mild Moderate Severe Colic (cramps) Absent Mild Moderate Severe Regurgitation Absent Mild Moderate Severe Average number of stools per day: What is the average consistency of the stools? Watery Soft, puddinglike Soft, formed Dry, formed Dry, hard pellets
22 FINDINGS ABOUT (FA) A dataset used to capture the findings about an event or intervention that cannot be represented within an event or intervention record or as a supplemental qualifier. Criteria 1) data that do not describe an Event or Intervention as a whole, 2) data ( about an Event or Intervention) having Qualifiers that can be represented in Findings variables (e.g., units, method), and 3) data ( about an Event or Intervention) that indicate the occurrence of related symptoms or therapies. FAOBJ: Used to describe the object or focal point of the findings observation that is represented by FATEST. Examples: an event such as VOMIT where the volume of Vomit is being measured by a VOLUME test.
23 GI TOLERANCE Visit 1 Baseline Gastrointestinal tolerance DOMAIN USUBJID FATESTCD FATEST FAOBJ FAORRES FAORRESU FA YYY A_COUNT Average Count STOOL 3 1/DAY FA YYY A_CONSIS Average Consistency STOOL WATERY FAOBJ= STOOL FATEST= Average Count Average number of stools per day: What is the average consistency of the stools? FATEST= Average consistency FAORRES FAORRES X 3 Watery Soft, puddinglike Soft, formed Dry, formed Dry, hard pellets
24 Updates over time (MAY 2016) Kindly provided by: Peter van Reusel Business & Decision Life Sciences Content Standards Technical Standards Semantics Therapeutic Areas ODM v1.3.1 v2.1 v3.0.3 v2.0 v3.0.1 ODM v1.1 / ODM v1.2 SDTM SDTM IG v3.1 Define.xml ODM v1.2.1 SDTM v1.1 SDTM IG v3.1.1 ODM v1.3 ADaM v2.0 v1.1 v1.1.1 SDTM v1.2 SDTM IG v3.1.2 CDASH v2.2 v3.0 ADaM v2.1 ADaM IG v3.0.2 ADaM Val. Checks Protocol Model
25 Updates over time (MAY 2016) Kindly provided by: Peter van Reusel Business & Decision Life Sciences COPD Content Standards Technical Standards Semantics Therapeutic Areas ODM v1.3.1 v3.0.3 v3.0.1 v3.0.2 ADaM Val. Checks Protocol Model Alzheimer SDM.XML SDTM v3.1.2 Am.1 ADaM Val. Checks v1.1 CDASH v1.1 SEND v3.0 Pain Devices Parkinson s Disease Tuberculosis Virology v3.2 SDTM v1.3 SDTM IG v3.1.3 ADaM Val. Checks v1.2 PRM Toolset CDASH UG v3.1 Asthma Alzheimer v1.1 PKD ODM v1.3.2 Define.xml v2.0 CDASH v1.2 SDTM v1.4 SDTM IG v3.2 SDTM Associated Persons IG CDASH E2B SAE IG ADaM MD Guide Influenza Diabetes QT Studies Cardiovascular Multiple Sclerosis Dataset-xml v4.0 ADaM IG v1.1 Protocol Concept Guide SEND IG v3.1 Virology v2.0 Hepatitis C Schizophrenia Dyslepidemia RDF UG RDF RG UG v2 Analysis Results Metadata SDTM v1.5 SDTM IG v3.3 SDTM Device Submission Pilot ADaM OCCDS V1.0 ADaM Validation Checks V1.3 SDTM Device IG v2.0 SDTM Pharmacogenomics IG Traumatic Brain Injury Breast cancer Diabetic Kidney Disease Define.xml v2.1 CTR-XML Define.xml IG Validation PROTOCOL.XML 1.0 SEND DART V1.0 SDTM IG v3.4 Batch 1 ADaM IG v1.2 ADaM IG 2.0 SEND IG v3.1 CDASH v2.0 CDASH v1.2 ADaM IG v
26 WHAT DOES THE FUTURE LOOK LIKE? Leverage value and increase capabilities Build on cross-functional collaborations and R&D data strategy Streamline with upstream standardization (CDASH/SDTM) Enable controlled data sharing and usage for Nutricia Research R&D community Incorporate & explore new sources of data There s more to come
27 THANK YOU Sophie Swinkels Marieke Abrahamse Lieke Egbers Daniela Cianci John Roth Remco van der Meer Michael Auld Lieke Gijsbers Lennert van der Zee Jules van der Zalm
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